Olkhovaya Anastasia Mikhailovna (Post-graduate student,
Moscow City University (MCU), Moscow, Russia
)
Romashkova Oxana Nikolaevna (Doctor of Engineering, Professor,
Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow, Russia
)
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This paper explores the integration of deep learning methods with virtual reality (VR) technologies for use on educational platforms. The primary focus is on developing a mathematical model that utilizes convolutional neural networks (CNN) for 3D model analysis and recurrent neural networks (RNN) for processing temporal data related to student actions. Algorithms for predicting student learning success and adapting educational materials to individual needs are described. Additionally, methods for generating 3D models based on textual descriptions are proposed to expand the platform's educational capabilities. An experimental evaluation of the proposed system was conducted, confirming its effectiveness in enhancing the quality and personalization of the learning process.
Keywords:deep learning, virtual reality, educational platforms, mathematical model, convolutional neural networks, recurrent neural networks, performance prediction, adaptation of educational materials, 3D model generation, personalized learning.
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Citation link:
Olkhovaya A. M., Romashkova O. N. MATHEMATICAL MODEL AND DEEP LEARNING ALGORITHMS FOR INTEGRATION WITH VR-TECHNOLOGIES ON EDUCATIONAL PLATFORMS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2024. -№11/2. -С. 115-119 DOI 10.37882/2223-2966.2024.11-2.24 |
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